Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations
Abstract Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitocho...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Publishing Group
2023-07-01
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| Series: | Experimental and Molecular Medicine |
| Online Access: | https://doi.org/10.1038/s12276-023-01011-2 |
| _version_ | 1797752832210763776 |
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| author | Zhiyang Xu Kaixiang Zhou Zhenni Wang Yang Liu Xingguo Wang Tian Gao Fanfan Xie Qing Yuan Xiwen Gu Shujuan Liu Jinliang Xing |
| author_facet | Zhiyang Xu Kaixiang Zhou Zhenni Wang Yang Liu Xingguo Wang Tian Gao Fanfan Xie Qing Yuan Xiwen Gu Shujuan Liu Jinliang Xing |
| author_sort | Zhiyang Xu |
| collection | DOAJ |
| description | Abstract Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients. |
| first_indexed | 2024-03-12T17:09:11Z |
| format | Article |
| id | doaj.art-55357745af34406c8dfe4c7a699b5918 |
| institution | Directory Open Access Journal |
| issn | 2092-6413 |
| language | English |
| last_indexed | 2024-03-12T17:09:11Z |
| publishDate | 2023-07-01 |
| publisher | Nature Publishing Group |
| record_format | Article |
| series | Experimental and Molecular Medicine |
| spelling | doaj.art-55357745af34406c8dfe4c7a699b59182023-08-06T11:07:51ZengNature Publishing GroupExperimental and Molecular Medicine2092-64132023-07-015571388139810.1038/s12276-023-01011-2Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutationsZhiyang Xu0Kaixiang Zhou1Zhenni Wang2Yang Liu3Xingguo Wang4Tian Gao5Fanfan Xie6Qing Yuan7Xiwen Gu8Shujuan Liu9Jinliang Xing10Department of Obstetrics and Gynecology, Xijing Hospital, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical UniversityDepartment of Obstetrics and Gynecology, Xijing Hospital, Fourth Military Medical UniversityDepartment of Obstetrics and Gynecology, Xijing Hospital, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Pathology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical UniversityDepartment of Obstetrics and Gynecology, Xijing Hospital, Fourth Military Medical UniversityState Key Laboratory of Cancer Biology and Department of Physiology and Pathophysiology, Fourth Military Medical UniversityAbstract Ovarian cancer (OC) is the most lethal gynecologic tumor and is characterized by a high rate of metastasis. Challenges in accurately delineating the metastatic pattern have greatly restricted the improvement of treatment in OC patients. An increasing number of studies have leveraged mitochondrial DNA (mtDNA) mutations as efficient lineage-tracing markers of tumor clonality. We applied multiregional sampling and high-depth mtDNA sequencing to determine the metastatic patterns in advanced-stage OC patients. Somatic mtDNA mutations were profiled from a total of 195 primary and 200 metastatic tumor tissue samples from 35 OC patients. Our results revealed remarkable sample-level and patient-level heterogeneity. In addition, distinct mtDNA mutational patterns were observed between primary and metastatic OC tissues. Further analysis identified the different mutational spectra between shared and private mutations among primary and metastatic OC tissues. Analysis of the clonality index calculated based on mtDNA mutations supported a monoclonal tumor origin in 14 of 16 patients with bilateral ovarian cancers. Notably, mtDNA-based spatial phylogenetic analysis revealed distinct patterns of OC metastasis, in which a linear metastatic pattern exhibited a low degree of mtDNA mutation heterogeneity and a short evolutionary distance, whereas a parallel metastatic pattern showed the opposite trend. Moreover, a mtDNA-based tumor evolutionary score (MTEs) related to different metastatic patterns was defined. Our data showed that patients with different MTESs responded differently to combined debulking surgery and chemotherapy. Finally, we observed that tumor-derived mtDNA mutations were more likely to be detected in ascitic fluid than in plasma samples. Our study presents an explicit view of the OC metastatic pattern, which sheds light on efficient treatment for OC patients.https://doi.org/10.1038/s12276-023-01011-2 |
| spellingShingle | Zhiyang Xu Kaixiang Zhou Zhenni Wang Yang Liu Xingguo Wang Tian Gao Fanfan Xie Qing Yuan Xiwen Gu Shujuan Liu Jinliang Xing Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations Experimental and Molecular Medicine |
| title | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
| title_full | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
| title_fullStr | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
| title_full_unstemmed | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
| title_short | Metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial DNA mutations |
| title_sort | metastatic pattern of ovarian cancer delineated by tracing the evolution of mitochondrial dna mutations |
| url | https://doi.org/10.1038/s12276-023-01011-2 |
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